1,545 research outputs found
A Fast Algorithm For Sparse Multichannel Blind Deconvolution
Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)We have addressed blind deconvolution in a multichannel framework. Recently, a robust solution to this problem based on a Bayesian approach called sparse multichannel blind deconvolution (SMBD) was proposed in the literature with interesting results. However, its computational complexity can be high. We have proposed a fast algorithm based on the minimum entropy deconvolution, which is considerably less expensive. We designed the deconvolution filter to minimize a normalized version of the hybrid l(1)/l(2)-norm loss function. This is in contrast to the SMBD, in which the hybrid l(1)/l(2)-norm function is used as a regularization term to directly determine the deconvolved signal. Results with synthetic data determined that the performance of the obtained deconvolution filter was similar to the one obtained in a supervised framework. Similar results were also obtained in a real marine data set for both techniques.811V7V16CAPESCNPqPetrobrasCoordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq
Buerger's disease manifesting nodular erythema with livedo reticularis
ArticleINTERNAL MEDICINE. 46(21):1815-1819(2007)journal articl
Dynamical brittle fractures of nanocrystalline silicon using large-scale electronic structure calculations
A hybrid scheme between large-scale electronic structure calculations is
developed and applied to nanocrystalline silicon with more than 10 atoms.
Dynamical fracture processes are simulated under external loads in the [001]
direction. We shows that the fracture propagates anisotropically on the (001)
plane and reconstructed surfaces appear with asymmetric dimers. Step structures
are formed in larger systems, which is understood as the beginning of a
crossover between nanoscale and macroscale samples.Comment: 10 pages, 4 figure
Fabrication of ZnSnP(2) thin films by phosphidation
ZnSnP(2) is a promising candidate as a solar absorbing material consisting of earth-abundant and low-toxic elements. In this study, the phosphidation method, where co-sputtered Zn–Sn thin films react with phosphorus gas, was adopted for fabricating ZnSnP(2) thin films. To establish the conditions for producing ZnSnP(2) thin films, we investigated the influence of phosphidation temperature on the product phases, and interpreted the experimental results using chemical potential diagrams of the Zn–Sn–P system. ZnSnP(2) thin films with a single phase were obtained by phosphidation at 500 °C under a phosphorus vapor pressure of 10[−2] atm. However, formation of ZnSnP(2)protrusions was observed on the surface of the thin films. Based on the experimental results and the chemical potential diagrams, it is indicated that un-reacted liquid Sn particles reacted with Zn and phosphorus gas to form ZnSnP(2) protrusions in a manner similar to the vapor-Liquid-Solid growth mode
Dynamics of Viscoplastic Deformation in Amorphous Solids
We propose a dynamical theory of low-temperature shear deformation in
amorphous solids. Our analysis is based on molecular-dynamics simulations of a
two-dimensional, two-component noncrystalline system. These numerical
simulations reveal behavior typical of metallic glasses and other viscoplastic
materials, specifically, reversible elastic deformation at small applied
stresses, irreversible plastic deformation at larger stresses, a stress
threshold above which unbounded plastic flow occurs, and a strong dependence of
the state of the system on the history of past deformations. Microscopic
observations suggest that a dynamically complete description of the macroscopic
state of this deforming body requires specifying, in addition to stress and
strain, certain average features of a population of two-state shear
transformation zones. Our introduction of these new state variables into the
constitutive equations for this system is an extension of earlier models of
creep in metallic glasses. In the treatment presented here, we specialize to
temperatures far below the glass transition, and postulate that irreversible
motions are governed by local entropic fluctuations in the volumes of the
transformation zones. In most respects, our theory is in good quantitative
agreement with the rich variety of phenomena seen in the simulations.Comment: 16 pages, 9 figure
Magnetic local time dependence of geomagnetic disturbances contributing to the AU and AL indices
The Auroral Electrojet (AE) indices, which are composed of four indices (AU, AL, AE, and AO), are calculated from the geomagnetic field data obtained at 12 geomagnetic observatories that are located in geomagnetic latitude (GMLAT) of 61.7°-70°. The indices have been widely used to study magnetic activity in the auroral zone. In the present study, we examine magnetic local time (MLT) dependence of geomagnetic field variations contributing to the AU and AL indices. We use 1-min geomagnetic field data obtained in 2003. It is found that both AU and AL indices have two ranges of MLT (AU: 15:00-22:00MLT, ~06:00 MLT; and AL: ~02:00 MLT, 09:00-12:00 MLT) contributing to the index during quiet periods and one MLT range (AU: 15:00-20:00MLT, and AL: 00:00-06:00 MLT) during disturbed periods. These results are interpreted in terms of various ionospheric current systems, such as, Sqp, Sq, and DP2
A Symmetry Property of Momentum Distribution Functions in the Nonequilibrium Steady State of Lattice Thermal Conduction
We study a symmetry property of momentum distribution functions in the steady
state of heat conduction. When the equation of motion is symmetric under change
of signs for all dynamical variables, the distribution function is also
symmetric. This symmetry can be broken by introduction of an asymmetric term in
the interaction potential or the on-site potential, or employing the thermal
walls as heat reservoirs. We numerically find differences of behavior of the
models with and without the on-site potential.Comment: 13 pages. submitted to JPS
Debiasing Machine Learning Models by Using Weakly Supervised Learning
We tackle the problem of bias mitigation of algorithmic decisions in a
setting where both the output of the algorithm and the sensitive variable are
continuous. Most of prior work deals with discrete sensitive variables, meaning
that the biases are measured for subgroups of persons defined by a label,
leaving out important algorithmic bias cases, where the sensitive variable is
continuous. Typical examples are unfair decisions made with respect to the age
or the financial status. In our work, we then propose a bias mitigation
strategy for continuous sensitive variables, based on the notion of endogeneity
which comes from the field of econometrics. In addition to solve this new
problem, our bias mitigation strategy is a weakly supervised learning method
which requires that a small portion of the data can be measured in a fair
manner. It is model agnostic, in the sense that it does not make any hypothesis
on the prediction model. It also makes use of a reasonably large amount of
input observations and their corresponding predictions. Only a small fraction
of the true output predictions should be known. This therefore limits the need
for expert interventions. Results obtained on synthetic data show the
effectiveness of our approach for examples as close as possible to real-life
applications in econometrics.Comment: 30 pages, 25 figure
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